PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks.
Minh N. VuMy T. ThaiPublished in: CoRR (2020)
Keyphrases
- probabilistic graphical models
- neural network
- graphical models
- first order logic
- application to image segmentation
- markov networks
- pattern recognition
- latent variables
- belief propagation
- conditional random fields
- approximate inference
- exact inference
- random variables
- soft computing
- parameter learning
- directed acyclic graph
- probabilistic inference
- probabilistic model
- hidden variables
- back propagation
- causal models
- np hard
- prior knowledge
- artificial neural networks
- fuzzy logic
- genetic algorithm
- message passing
- knowledge representation
- maximum likelihood
- bayesian networks